Expression profile based gene clusters for ischemic stroke detection.

In microarray studies alterations in gene expression in circulating leukocytes have shown utility for ischemic stroke diagnosis. We studied forty candidate markers identified in three gene expression profiles to (1) quantitate individual transcript expression, (2) identify transcript clusters and (3) assess the clinical diagnostic utility of the clusters identified for ischemic stroke detection. Using high throughput next generation qPCR 16 of the 40 transcripts were significantly up-regulated in stroke patients relative to control subjects (p<0.05). Six clusters of between 5 and 7 transcripts were identified that discriminated between stroke and control (p values between 1.01e-9 and 0.03). A 7 transcript cluster containing PLBD1, PYGL, BST1, DUSP1, FOS, VCAN and FCGR1A showed high accuracy for stroke classification (AUC=0.854). These results validate and improve upon the diagnostic value of transcripts identified in microarray studies for ischemic stroke. The clusters identified show promise for acute ischemic stroke detection.